Yu‐An Chen

The paper maps oxidative stress response in TNBC using single-cell and spatial data, identifying GCLC+ mesenchymal tumor cells linked to better patient outcomes.

This paper introduces a method that combines autoencoders with segmentation to improve single-cell analysis of multiplexed tissue images by capturing morphology and reducing signal spillover.

The paper maps spatial patterns of tumor cell dedifferentiation and plasticity in melanoma by analyzing RNA and protein expression across 300 histological domains.

This study uses spatial profiling to show immune suppression and microenvironment changes in fallopian tube precursors of high-grade serous ovarian cancer.

The paper identifies a subset of mismatch repair proficient colorectal cancers with high immune infiltration that may benefit from immune checkpoint inhibitors, using spatial profiling and genomics.

Galaxy-ME is a web-based software hub for analyzing and visualizing multiplex tissue imaging datasets, demonstrating its utility on normal and cancerous tissue data.

ASHLAR is a Python tool that stitches and registers highly multiplexed whole slide images to generate accurate mosaics, outperforming existing software.

MCMICRO processes multiplexed tissue images into single-cell data, demonstrating its versatility across different tissues and imaging platforms.